About Me
Hey! My name is Andre. I'm a final year undergraduate studying Mathematics & Computer Science at the National University of Singapore (NUS).
Machine learning is an exciting field at the intersection of mathematical theory (brutal math courses finally paying off.. *_*) and software engineering. There's no shortage of groundbreaking research in the ML landscape, and I desire to be among those who bring these innovations into real-world applications.
I am now particularly interested in the intricacies of parallelism in training/inference optimization and distributed systems. I aspire to design the infrastructure of next-generation ML systems and pipelines.
Beyond academia, I am a casual climber (an occasional diver, and avid backpacker) and I am part of the university's Mountaineering club and Climbing club. Together with a couple of πΈπ°π―π₯π¦π³π§πΆπππΊ π§πΆπ―-ππ°π·πͺπ―π¨ π€πΆπ€π¬π°π°π΄, we scaled the Himalayas and it was simply fantastic!
Ongoing
PaperDebugger: ππ³πͺπ΅π¦ ππ¦π΅π΅π¦π³, ππ¦π΅ ππ€π€π¦π±π΅π¦π₯
Originally my Final Year Thesis, this work has grown into a self-driven production system: a multi-agent platform integrated with Overleaf for LaTeX-aware debugging and revision. Our work is open source! https://github.com/PaperDebugger/paperdebugger
Machine Learning Research @ Xtra Computing, NUS
Part of Prof He Bingsheng's research group, focusing on distributed ML systems and adaptations of the transformer architecture. Fortunate enough to make some publications along the way!
Data Structures & Algorithms Teaching Resource
My stint as a lead TA for CS2040s (Discrete Structures & Algorithms) has convinced several capable and passionate ex-students to join me in developing this teaching resource for future cohorts.
Experience
Software Engineer Intern @ JPMorganChase, June 2025 - August 2025
The bank was in its Agentic AI phase, so I learnt, built, and extended custom MCP integration and validation logic for backend. My primary work was ensuring equity market data was ready for downstream use.
Software Engineer Intern @ QuantEdge, May 2025 - June 2025
Software Engineering meets Quantitative Trading - Learnt how to support the trading team. Taught me zero-tolerance engineering.
Backend Engineer Intern @ Apple, January 2025 - May 2025
Gained practical knowledge on system design and was taught what simple, reliable, sustainable, and fault-tolerant systems look like.
Machine Learning Engineer Intern @ Pints.ai (Singapore), August 2024 - December 2024
Worked on finetuning LLMs using data and model parallelism techniques to contend with larger models at lower cost. Also learnt to design, build, and deploy ML pipelines in production. I trace my origins here.
Machine Learning Engineer Intern @ ASTRI (Hong Kong, SAR), June 2024 - August 2024
Learnt ML production and deployment lifecycle, and worked on Quant Research projects affiliated with QRT.
School of Computing (NUS), August 2022 - August 2024
Teaching Assistant for CS1010s (Programming Methodology in Python) and CS2040s (Data Structures and Algorithms); Won a teaching excellence award!
Latest Posts
Sisyphus' Revolt
What's The Point of It All?
Hong Kong: The City That Never Sleeps
Bustling city. Classy heels. Dazzling lights. Furious pace. Utter shit.
Norway ain't no way!
No way ain't Norway.
Krabi Once More: Old Friends, New Connections
Krabi '24 β When a Year of Effort Finally Paid Off
Skills
Languages (Ordered by proficiency)
Python, Java, C++, Go, TypeScript
Libraries
TensorFlow, PyTorch, Scikit-learn, OpenCV, pandas, NumPy
Notable LLM Frameworks
vLLM, llama.cpp, DeepSpeed, Lightning AI, LitGPT, LangChain
Data Processing/Databases
PostgreSQL, Spark, Flink, Kafka
Backend
Docker, Django, FastAPI, Spring Boot, Express, Nodejs